How Sarah Bernstein is building learning into every redesigned workflow

Meet Sarah Bernstein, VP, Organizational Transformation and Capability Development at Lumen

Sarah leads organizational transformation and capability development at Lumen Technologies, which is transforming from a legacy telco into a digital network service provider across every function.

She brings work redesign and employee learning into the same conversation. Changing a workflow also changes what people need to know, how they apply judgment and what leaders should expect of them.

Lumen’s AI journey began with teams identifying opportunities across the business. Sarah saw that disconnected use cases needed a shared view of the work and a plan for how people’s roles would change.

Her answer pairs detailed workflow redesign with learning built at the same time, so people know their new way of working from day one rather than weeks after deployment.

Subtask depth is what makes reimagination real

Task-level data shows where AI potential exists. Subtask-level data shows how to actually rebuild the work. “There’s a part of me that wishes you could go faster,” Sarah says, “but when you think about reimagining how we’ve worked for different decades, you need to understand what are you truly trying to design.” Sarah brought functional leaders together with Reejig and Microsoft to map work and redesign workflows. In hiring, for example, mapping each step from job description to onboarding showed where an agent could assist and where context at each handoff mattered. Without that detail, an agent build is incomplete.

Subtask depth is what makes reimagination real

Task-level data shows where AI potential exists. Subtask-level data shows how to actually rebuild the work. “There’s a part of me that wishes you could go faster,” Sarah says, “but when you think about reimagining how we’ve worked for different decades, you need to understand what are you truly trying to design.”

Sarah brought functional leaders together with Reejig and Microsoft to map work and redesign workflows. In hiring, for example, mapping each step from job description to onboarding showed where an agent could assist and where context at each handoff mattered. Without that detail, an agent build is incomplete.

Accelerating early careers

Sarah sees AI as a way to accelerate early-career employees, not replace them. If agents handle repetitive execution, people can build judgment and domain understanding sooner. “Can I, with AI, move them through what would have been a year-over-year journey?” The opportunity also lies in pairing the expertise of long-tenured domain specialists with the AI-first instincts of people just entering the workforce.